Faceted search, also called faceted navigation or faceted browsing, is a technique for accessing information organized according to a faceted classification system. In a context of a search systems accessing a vast amount of information, producing a large number of search results such a faceted classification system allows users to explore and refine the search results by applying suitable filters. Such a faceted classification system enables the possibility to classify search results dynamically, rather than in a single, predetermined, taxonomic order. Facets correspond to properties of the search results. These facets can for example be determined in function of pre-existing fields in a database, that form properties of the search results. Such facets could be determined in function of database fields, such as for example be author, description, language, dates, prices, technical features, etc. This allows for example to refine search results resulting from a query “digital camera” on a database storing items sold through an online shop to be refined by using the following facets, “price”, “resolution”, “brand”, etc. Alternatively or additionally facets could also be determined in function of analysis of the text content related to a search result for example by using entity extraction techniques. Faceted search in this way enables users to navigate a multi-dimensional information space by combining text search with a progressive adaptation of choices in each dimension by means of these facets.
A system for visualisation of search result facets is for example known from US2007179952. Time based facets, which are search result properties that can qualify as dates, time periods, etc. are represented in a linear fashion, for example by means of a time line. Location based facets, which are search result properties that can qualify as countries, gps coordinates, addresses, etc. are for example represented on a map.
Further systems allowing for visualisation of search result facets are generally known from online shops, in which a range of values for a “price” facet is represented as a slider bar by which a minimum and/or maximum value can be set by the user for allowing further filtering of the search results.
Such systems allow for an efficient representation of the facets, especially in a situation where the range of possible values of the facets is large and/or where a textual representation, for example in the form of lists as known from US20070283259, does not clearly show the possible relationship between different values or ranges of values of the facets. These known systems function well within the context of for example an online shop as the properties of the search results qualifying as facets are well known and a suitable visualisation can be linked to them. The same holds for relatively simple facets such as time based facets or location based facets as known from US2007179952.
However, in the context of a search system covering a plurality of large scale databases, in which new databases are added and removed over time and each of these large scale databases themselves evolving over time, such prior art systems present several difficulties. Such search systems are for example in use in the context of pharmaceutical companies in which researchers make use of information contained in large number of databases, for example freely accessible external databases, external databases provided by commercial providers, in-company databases, etc. providing data about for example genes, proteins, clinical data, patient histories, clinical trials, molecules, etc. Every time a new database is made accessible or every time the setup of an existing database is changed, the search system, extensive programming and configuration is necessary in order to determine the correct way of visualisation for the relevant facets of the search results. Furthermore determination of the preferred way of visualisation of such complex data is not an easy task for a programmer to perform and often requires extensive consultation of end users and/or results in a sub-optimal user experience.
There still exists a need to improve flexibility and efficiency of the visualisation of faceted search results in the context of such a large scale, complex faceted search system.